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DEploying High ValuE LOngitudinal Population-Based dAta in Dementia Research (DEVELOP AD Research)

DEploying High ValuE LOngitudinal Population-Based dAta in Dementia Research (DEVELOP AD Research)
在痴呆症研究中部署基于人群的高价值纵向数据(DEVELOP AD 研究)
批准号:
10265431
负责人:
KENNETH E. COVINSKY
金额:
$239.02万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-09-30 至 2025-05-31

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中文摘要
翻译
项目概要 随着老龄化金字塔的形成,医疗保健系统面临着前所未有的老年人数量 严重的慢性疾病、不断上升的费用以及可用护理人员的减少。这些挑战是巨大的 在阿尔茨海默氏病和相关痴呆症(ADRD)的情况下,这种现象会被放大。与 ADRD 一起生活是 其特点是身体和心理上的痛苦,患者的护理目标与治疗目标之间不匹配 接受的治疗;对家庭和卫生系统造成沉重的身体、心理和经济负担。 该计划项目在痴呆症研究中部署基于人口的高价值纵向数据 (发展广告研究),通过利用丰富的基于人口的数据来开发新的领域 对痴呆症的全面纵向了解将更好地为临床和政策干预提供信息 改善痴呆症患者及其家人的医疗保健。 方法论的限制限制了检查医学、 已知影响患者健康、医疗保健以及生死质量的社会和系统因素 失智。需要招募足够大的样本来解释总体的异质性, 从不同护理环境中的患者和护理人员收集数据的必要性、收集困难 由于预算和主要数据收集工作的限制而导致的健康数据的社会决定因素,以及 超过标准 5 年拨款资助期限的疾病持续时间限制了回答的能力 重要的问题。 健康与退休研究 (HRS) 和国家健康与老龄化趋势研究 (NHATS) 正在进行的 NIA 资助的基于人群的研究包含丰富的纵向患者和家庭健康、社会、 和经济数据,并通过与 CMS 索赔的联系,获得有关医疗服务的综合信息 利用率和成本。由于其成熟度、参与者数量、保留率、抽样框架和 用于识别痴呆症的经过验证的算法,两个数据集现在都能够提供足够的样本量, 变量和纵向随访,以开始解决痴呆症研究中的现有差距。编组预 现有资源和项目研究人员之间高效的合作,我们通过以下方式开辟了新天地: 提出综合研究来检验医学、社会和系统复杂的纵向相互作用 已知影响痴呆症患者的健康、医疗保健以及生活质量和死亡的因素。我们的五个 研究项目解决了痴呆症科学中的主要问题,其答案需要使用 现在可通过 NHATS 和/或 HRS 获取基于人口的数据。我们的两个资源核心支持 每个研究项目所需的复杂分析,整合和协调研究活动,传播 发现和数据资源,包括编程代码和数据字典,创建一个研究平台 支持早期研究人员,并确定未来的方向和研究合作。
英文摘要
PROJECT SUMMARY As the aging pyramid squares, healthcare systems face unprecedented numbers of older adults living with serious chronic illness, escalating costs, and reductions in available caregivers. These challenges are greatly magnified in the setting of Alzheimer’s disease and related dementias (ADRD). Living with ADRD is characterized by physical and psychosocial suffering, mismatches between patient goals of care and treatments received; high physical, psychological, and financial burdens on families and the health system. This program project, Deploying High Value Longitudinal Population-based data in Dementia Research (DEVELOP AD RESEARCH), breaks new ground by employing rich population-based data to develop a comprehensive longitudinal understanding of dementia that will better inform clinical and policy interventions and improve healthcare for persons with dementia and their families. Methodological constraints have limited the ability to examine the complex longitudinal interplay of medical, social, and system factors known to influence health, healthcare, and quality of life and death for persons with dementia. The need to enroll samples large enough to account for the population’s heterogeneity, the necessity of gathering data from patients and caregivers across diverse care settings, difficulties collecting social determinants of health data due to budgetary and primary data collection effort constraints, and a duration of illness that exceeds standard 5-year grant funding periods have limited the ability to answer important questions. The Health and Retirement Study (HRS) and the National Health and Aging Trends Study (NHATS) are ongoing NIA funded population-based studies that contain rich longitudinal patient and family health, social, and economic data and, through their linkages to CMS claims, comprehensive information on health service utilization and costs. Due to their maturity, numbers of participants, retention rates, sampling frames, and validated algorithms for identifying dementia, both datasets are now able to provide sufficient sample sizes, variables, and longitudinal follow-up to begin to address existing gaps in dementia research. Marshalling pre- existing resources and highly productive collaborations among project investigators, we break new ground by proposing integrated research that examines the complex longitudinal interplay of medical, social, and system factors known to influence health, healthcare, and quality of life and death for persons with dementia. Our five research projects address major questions in dementia science whose answers demand the use of the population-based data now available through NHATS and/or HRS. Our two resource cores support the complex analytics required of each research project, integrate and coordinate research activities, disseminate findings and data resources including programming code and data dictionaries, create a platform of research to support early-stage investigators, and identify future directions and research collaborations.
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DEploying High ValuE LOngitudinal Population-Based dAta in Dementia Research (DEVELOP AD Research)
DEploying High ValuE LOngitudinal Population-Based dAta in Dementia Research (DEVELOP AD Research)
UCSF Older Americans Independence Center
UCSF Older Americans Independence Center
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